COST REDUCTION IN THE MICROPROPAGATION OF SOLANUM LYCOPERSICUM L. VAR. CERASIFORME

The aim of this study was to establish a low cost alternative protocol for the micropropagation of Solanum lycopersicum L. var. cerasiforme. In the in vitro establishment, culture media containing P.A. and commercial sucrose and varying concentrations of corn starch and agar were tested. The replacement of physical sterilization for chemical sterilization was also evaluated. In the multiplication step, the medium was supplemented with agar and / or corn starch and commercial sucrose. For rooting, medium with commercial sucrose supplemented with agar and / or starch was used. Subsequently, the microplants were acclimatized in a greenhouse. The results allow us to conclude that the cost reduction in the micropropagation of cherry tomato is obtained by the substitution of P.A. sucrose by commercial sucrose, partial (establishment and multiplication) and total (rooting) substitution of agar by corn starch and also by the use of chemical sterilization of the medium. The microplants obtained from this protocol were successful in acclimatization step.O objetivo deste estudo foi estabelecer um protocolo alternativo de baixo custo para micropropagação de Solanum lycopersicum L. var. cerasiforme, conhecida popularmente como tomate cereja. No estabelecimento in vitro foram testados meios de cultura contendo sacarose P.A. e comercial e concentrações variadas de amido de milho e ágar. Também avaliou-se a substituição da esterilização física pela esterilização química. Na etapa de multiplicação o meio foi suplementado com ágar e/ou amido de milho e sacarose comercial. Para o enraizamento utilizou-se meio isento de regulador com sacarose comercial suplementado com ágar e/ou amido. As microplantas foram transplantadas para terra vegetal e aclimatizadas em casa de vegetação. Os resultados permitem concluir que a redução de custos na micropropagação do tomate cereja é obtida pela substituição de sacarose P.A. pela sacarose comercial, substituição parcial (estabelecimento e multiplicação) e total (enraizamento) de ágar por amido de milho e pela utilização de esterilização química do meio

Gelation of Culture Medium with K-Carrageenan Improves and Reduces the Cost of in vitro Propagation of Comanthera mucugensis (Giul.) L. R. Parra & Giul

Abstract In vitro multiplication is the main method for seedling production of Comanthera mucugensis, an endangered ornamental plant. The technique consists of cultivating plant tissues under aseptic conditions, controlled environment, and using appropriate culture medium. The physical characteristics of the medium are mainly determined by the presence of a gelling agent. Agar is the most used substance on the in vitro cultivation of C. mucugensis, however, it is one of the most costly components to manufacture the medium. The objective of the present study was to evaluate the effect of κ-carrageenan as an alternative gelling agent in the propagation of C. mucugensis. The seeds and stem explants were cultured on medium gelled with agar or κ-carrageenan, both at 7 g L-1 concentration. The results indicated that the plants established in medium with κ-carrageenan presented an increase in length and induced formation of shoots. Direct organogenesis was also improved with the use of this gelling agent. In comparison, agar culture presented the lowest rate of direct regeneration and the lowest number of shoots. In addition, gelation with κ-carrageenan was efficient in increasing the frequency of callogenesis, as well as, the highest callus regeneration and number of shoots per callus. Rooting was not affected by the type of gelling agent. The substitution of agar for κ-carrageenan can represent a reduction of 23.2% in the cost of manufacturing the culture medium for in vitro propagation of C. mucugensis

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost